A Literature Review on Clickbait Detection Techniques for Social Media

The rising popularity of social media offers advantages like cost-effectiveness, user-friendliness, and rapid content consumption. However, this increase in popularity has led to a new issue known as clickbait. Clickbait refers to the deliberate spreading of misleading information to attract reader interest. This tactic draws users to click on and interact with content in various formats, including audio, video, text, and images. Consequently, users often find themselves watching a video that fails to deliver the promised information in its title or thumbnail. Clickbait thumbnails typically feature exaggerated or deceptive visuals to attract viewers into clicking. While these can significantly boost click-through rates and web traffic, they risk spreading false or low-quality content, diminishing online information sources' trust and credibility. As a result, researching methods to identify clickbait on social media is becoming more critical. In this study, the author conducts a literature review to evaluate the effectiveness and F1 score of different clickbait detection techniques.